Source code for pycif.plugins.transforms.system.array2sampled.forward

import numpy as np
import xarray as xr

from logging import warning




def forward(
        transform,
        inout_datastore,
        controlvect,
        obsvect,
        mapper,
        di,
        df,
        mode,
        runsubdir,
        workdir,
        onlyinit=False,
        **kwargs
):
    if onlyinit:
        return

    ddi = min(di, df)
    for trid_in, trid_out in zip(mapper["inputs"], mapper["outputs"]):
        xmod_in = inout_datastore["inputs"][trid_in][ddi]
        xmod_out = inout_datastore["outputs"][trid_out][ddi]

        t = xmod_out["metadata"]["tstep"].astype(int).values
        i = xmod_out["metadata"]["i"].astype(int).values
        j = xmod_out["metadata"]["j"].astype(int).values

        # Deal with levels differently
        if xmod_in["spec"].shape[1] == 1:
            lev = (0. * i).astype(int)

        else:
            lev = xmod_out["metadata"]["level"].astype(int).values

        columns = ["spec"] if mode == "fwd" else ["spec", "incr"]
        for c in columns:
            if c not in xmod_in:
                continue

            xmod_out[("maindata", c)] = xmod_in[c].isel(
                lat=xr.DataArray(i),
                lon=xr.DataArray(j),
                time=xr.DataArray(t),
                lev=xr.DataArray(lev)).data